Relationships between reading, tracing and writing skills in introductory programming
Open accessAbstract
This study analyzed student responses to an examination, after the students had completed one semester of instruction in programming. The performance of students on code tracing tasks correlated with their performance on code writing tasks. A correlation was also found between performance on "explain in plain English" tasks and code writing. A stepwise regression, with performance on code writing as the dependent variable, was used to construct a path diagram. The diagram suggests the possibility of a hierarchy of programming related tasks. Knowledge of programming constructs forms the bottom of the hierarchy, with "explain in English", Parson's puzzles, and the tracing of iterative code forming one or more intermediate levels in the hierarchy.
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Prior work in introductory programming has shown that code-reading and tracing skills are essential to problem-solving activities including code-writing.
“Prior work in introductory programming has shown that code-reading and tracing skills are essential to problem-solving activities including code-writing [49,55,57].”
From Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming (2023) · cites this paper as [57]
The Discussion (§6) reports significant associations between code-reading, code-tracing, and code-writing performance. But the paper presents a hierarchy of skills as a possibility, not a demonstrated necessity; its findings do not establish that reading and tracing are essential to problem-solving activities generally. (LLM, conf=0.88)
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Cites
(2001) · Cited by 13,930 · see citing works
Probabilistic Models for Some Intelligence and Attainment Tests
Psychology, M. (1961) · Information and Control · doi:10.1016/s0019-9958(61)80061-2 · Cited by 6,936 · see citing works
Efficient tests for normality, homoscedasticity and serial independence of regression residuals.
Jarque, C. M., & Bera, A. K. (1980) · Economics Letters · doi:10.1016/0165-1765(80)90024-5 · Cited by 4,338 · see citing works
A Rating Formulation for Ordered Response Categories
Andrich, D. (1978) · Psychometrika · doi:10.1007/bf02293814 · Cited by 2,984 · see citing works
Evaluating the Quality of Learning: The Solo Taxonomy : Structure of the Observed Learning Outcome
Biggs, J., & Collis, K. F. (1977) · Cited by 1,087 · see citing works
When novices surpass experts: The difficulty of a task may increase with expertise.
Adelson, B. (1984) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/0278-7393.10.3.483 · Cited by 396 · see citing works
Not seeing the forest for the trees
Lister, R., Simon, B., Thompson, E., Whalley, J. L., & Prasad, C. (2006) · ACM SIGCSE Bulletin · doi:10.1145/1140123.1140157 · Cited by 266 · see citing works
Self-citationBloom's Taxonomy for CS Assessment
Thompson, E., Luxton-Reilly, A., Whalley, J. L., Hu, M., & Robbins, P. (2008) · University of Birmingham Research Portal (University of Birmingham) · doi:10.5555/1379249.1379265 · Cited by 203 · see citing works
Self-citationParson's programming puzzles: a fun and effective learning tool for first programming courses
Parsons, D., & Haden, P. (2006) · Australasian Computing Education Conference · Cited by 195 · see citing works
Whalley, J. L., Lister, R., Thompson, E., Clear, T., Robbins, P., Kumar, P. K. A., & Prasad, C. (2006) · Tuwhera (Auckland University of Technology) · Cited by 193 · see citing works
Self-citationWhat do novices learn during program comprehension?
Corritore, C. L., & Wiedenbeck, S. (1991) · International Journal of Human-Computer Interaction · doi:10.1080/10447319109526004 · Cited by 112 · see citing works
On blooming first year programming, and its blooming assessment
Lister, R. (2000) · doi:10.1145/359369.359393 · Cited by 109 · see citing works
Self-citationCharacteristics of the mental representations of novice and expert programmers: an empirical study
Wiedenbeck, S., Fix, V., & Scholtz, J. C. (1993) · International Journal of Man-Machine Studies · doi:10.1006/imms.1993.1084 · Cited by 100 · see citing works
The many ways of the BRACElet project
Whalley, J. L., Clear, T., & Lister, R. (2007) · UTS ePRESS (University of Technology Sydney) · Cited by 18 · see citing works
Self-citationSpinellis, D. D. (2003) · Queue · doi:10.1145/957717.957782 · Cited by 17 · see citing works
Code classification as a learning and asssessment exercise for novice programmers
Thompson, E., Whalley, J. L., Lister, R., & Simon, B. (2006) · UTS ePRESS (University of Technology Sydney) · Cited by 13 · see citing works
Self-citationReport on the fourth BRACElet workshop
Whalley, J. L., & Robbins, P. (2007) · Journal of applied computing and information technology · Cited by 10 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 2
- [7]7. Biggs, J. B. & Collis, K. F. Evaluating the quality of learning: The SOLO taxonomy (Structure of the Observed Learning Outcome). New York, Academic Press, 1982.
- [11]11. Philpott, A, Robbins, P., and Whalley, J. Accessing The Steps on the Road to Relational Thinking. Proceedings of the 20 th Annual NACCQ.
Cited by
Sorted by citations
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Luxton-Reilly, A., Simon, Al-Bluwi, I., Becker, B. A., Giannakos, M. N., Kumar, A. N., Ott, L. M., Paterson, J. H., Scott, M., Sheard, J., et al. (2018) · doi:10.1145/3293881.3295779 · Cited by 511 · see citing works
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A closer look at tracing, explaining and code writing skills in the novice programmer
Venables, A. T., Tan, G., & Lister, R. (2009) · doi:10.1145/1584322.1584336 · Cited by 188 · see citing works
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Falkner, K. E. K., & Sheard, J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.016 · Cited by 27 · see citing works
Supporting skill integration in an intelligent tutoring system for code tracing
Huang, Y., Brusilovsky, P., Guerra, J., Koedinger, K., & Schunn, C. (2023) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12757 · Cited by 25 · see citing works
Effects, Experiences and Feedback from Studies of a Program Visualization Tool
Kaila, E., Rajala, T., Laakso, M., & Salakoski, T. (2009) · Informatics in Education · doi:10.15388/infedu.2009.02 · Cited by 25 · see citing works
Code comprehension problems as learning events
DeLyser, L. A., Stehlik, M., & Carver, S. M. (2012) · ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE) · doi:10.1145/2325296.2325319 · Cited by 25 · see citing works
Evaluating the Effectiveness Roles of Variables in the Novice Programmers Learning
Shi, N., Cui, W., Zhang, P., & Sun, X. (2017) · Journal of Educational Computing Research · doi:10.1177/0735633117707312 · Cited by 25 · see citing works
Effects of course-long use of a program visualization tool
Kaila, E., Rajala, T., Laakso, M., & Salakoski, T. (2010) · doi:10.5555/1862219.1862234 · Cited by 25 · see citing works
Simon, & Snowdon, S. (2011) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/2016911.2016931 · Cited by 25 · see citing works
Qualitative Methods for Computing Education
Tenenberg, J. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.008 · Cited by 24 · see citing works
Haden, P. (2019) · Cambridge University Press eBooks · doi:10.1017/9781108654555.006 · Cited by 26 · see citing works
CrossCode: Multi-level Visualization of Program Execution
Hayatpur, D., Wigdor, D., & Xia, H. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581390 · Cited by 23 · see citing works
- Authors
- Lopez, M., Whalley, J., Robbins, P., & Lister, R.
- Affiliations
- Manukau Institute of Technology (NZ)
- Auckland University of Technology (NZ)
- University of Technology Sydney (AU)
- Venue
- Proceedings of the Fourth international Workshop on Computing Education Research
- Publisher
- ACM
- Published
- 2008-09-06
- Pages
- 101-112
- OpenAlex
- W2165365113
- Semantic Scholar
- 2cab0a77f6ed8fc4ca1ca1ec9782dfc4d36f2254
- Cited by
- 363
- References
- 17
- Citations by year
- 2026: 9 · 2025: 17 · 2024: 26 · 2023: 29 · 2022: 25 · 2021: 28 · 2020: 29 · 2019: 60 · 2018: 23 · 2017: 18 · 2016: 14 · 2015: 12 · 2014: 12 · 2013: 11 · 2012: 17
- FWCI
- 11.71
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Locations
- ACM Conference on International Computing Education Research (ICER) (publishedVersion)
- UTS ePRESS (University of Technology Sydney) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Artificial Intelligence › Educational Robotics and Engineering
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Keywords
- introductory programming, code tracing, writing software, reading skills, programming constructs, task hierarchy, student performance
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